Open AccessYOPCB: A Single-stage Multi-attention Detection Network for PCB Surface Defects
Author(s) -
Yi Ge,
Yang Zhou,
Jiale Yang,
Yue Zhang,
Fei Xie,
Xiaobo Tang
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2203/1/012069
Subject(s) - miniaturization , printed circuit board , welding , production efficiency , component (thermodynamics) , industrial production , process (computing) , electronic component , computer science , electronic engineering , process engineering , engineering , mechanical engineering , electrical engineering , physics , keynesian economics , economics , thermodynamics , operating system
With the miniaturization of electronic components, printed circuit boards (PCB) as a important component of them has become more and more complex and exquisite. Different defects in PCB can be found in modern industrial manufacture, such as lack of weld, lacking components, continuous welding, and the color ring resistance, resulting in low production. Accordingly, it is necessary to achieve the high rate of precision and efficiency when defecting during PCBs industrial production process. Considering that existing detection of PCB defects have a low efficiency, we propose an improved model YOPCB defecting PCB surface defects. Our improved model can achieve the precision of 97.6% mAP, which means our method is more efficient.